A personalized prediction model for urinary tract infections in type 2 diabetes mellitus using machine learning.

Patients with type 2 diabetes mellitus (T2DM) are at higher risk for urinary tract infections (UTIs), which greatly impacts their quality of life. Developing a risk prediction model to identify high-risk patients for UTIs in those with T2DM and assisting clinical decision-making can help reduce the incidence of UTIs in T2DM patients. To construct the predictive model, potential relevant variables were first selected from the reference literature, and then data was extracted from the Hospital Information System (HIS) of the Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital for analysis. The data set was split into a training set and a test set in an 8:2 ratio. To handle the data and establish risk warning models, four imputation methods, four balancing methods, three feature screening methods, and eighteen machine learning algorithms were employed. A 10-fold cross-validation technique was applied to internally validate the training set, while the bootstrap method was used for external validation in the test set. The area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to evaluate the performance of the models. The contributions of features were interpreted using the SHapley Additive ExPlanation (SHAP) approach. And a web-based prediction platform for UTIs in T2DM was constructed by Flask framework. Finally, 106 variables were identified for analysis from a total of 119 literature sources, and 1340 patients were included in the study. After comprehensive data preprocessing, a total of 48 datasets were generated, and 864 risk warning models were constructed based on various balancing methods, feature selection techniques, and a range of machine learning algorithms. The receiver operating characteristic (ROC) curves were used to assess the performances of these models, and the best model achieved an impressive AUC of 0.9789 upon external validation. Notably, the most critical factors contributing to UTIs in T2DM patients were found to be UTIs-related inflammatory markers, medication use, mainly SGLT2 inhibitors, severity of comorbidities, blood routine indicators, as well as other factors such as length of hospital stay and estimated glomerular filtration rate (eGFR). Furthermore, the SHAP method was utilized to interpret the contribution of each feature to the model. And based on the optimal predictive model a user-friendly prediction platform for UTIs in T2DM was built to assist clinicians in making clinical decisions. The machine learning model-based prediction system developed in this study exhibited favorable predictive ability and promising clinical utility. The web-based prediction platform, combined with the professional judgment of clinicians, can assist to make better clinical decisions.

Laboratory Study on Disconnection Events in Comets.

When comets interacting with solar wind, straight and narrow plasma tails will be often formed. The most remarkable phenomenon of the plasma tails is the disconnection event, in which a plasma tail is uprooted from the comet's head and moves away from the comet. In this paper, the interaction process between a comet and solar wind is simulated by using a laser-driven plasma cloud to hit a cylinder obstacle. A disconnected plasma tail is observed behind the obstacle by optical shadowgraphy and interferometry. Our particle-in-cell simulations show that the difference in thermal velocity between ions and electrons induces an electrostatic field behind the obstacle. This field can lead to the convergence of ions to the central region, resulting in a disconnected plasma tail. This electrostatic-field-induced model may be a possible explanation for the disconnection events of cometary tails.

Phase control requirements of high intensity laser beam combining.

Aiming at getting the general requirements of the beam combine for ignition scale laser facilities, the analytical expressions including the factors affecting the combine results are derived. The physical meanings of every part are illustrated. Based on these expressions, the effects of the factors, including the beam configuration, piston error, and tip/tilt error, are studied analytically and numerically. The results show that the beam configuration cannot affect the Strehl ratio (SR) of the combined beam, but it influences the FWHM of the main peak and the ratio of the main peak and the side peak. The beam separation should be no more than 1.24 times the individual beam width for the multibeam combine, and be close to the individual beam width for the two-beam combine as much as possible. The piston error can change the characteristics of the combine beam focus, including the peak intensity, the focal spot morphology, the fractional energy contained within a certain area, and the center of mass. For the two-beam combine, a piston error less than 2π/5 rad is suitable, and for the multibeam combine, the standard deviation of the piston error should be no more than 2π/10 rad. The tip/tilt error has a great influence on the combined results. It affects the superposition degree of the focal spots of the combined elements directly. A requirement of 0.5~1 µrad for the standard deviation of the tip/tilt error is adequate.

Fractional Fourier transform of flat-topped multi-Gaussian beams.

The fractional Fourier transform (FRFT) of the flat-topped multi-Gaussian beam (FMGB) is investigated based on the three kinds of FRFT optical systems: Lohmann I, Lohmann II, and quadratic graded-index systems. The analytical expressions for the FRFT of the FMGB are derived based on the propagation of the FMGB through the three systems. By introducing a hard-edge aperture function, the analytical expressions for the FRFT of the FMGB carried out by the apertured FRFT optical systems are presented. The FRFT characteristics of the FMGB for the three kinds of FRFT optical systems with and without apertures are discussed in detail. Results show that the three types of FRFT optical systems have the same function when the apertures are ignored but that significantly different characteristics are exhibited when the apertures appear.

Propagation of flat-topped multi-Gaussian beams through an apertured ABCD optical system.

The generalized analytical expression for the propagation of flat-topped multi-Gaussian beams through a misaligned apertured ABCD optical system is derived. Using this analytical expression, the propagation characteristics of flat-topped multi-Gaussian beams through a spatial filter are investigated. The analytical formula of the electric field distribution in the focal plane is also derived for revealing the effects of the misalignment parameters clearly. It is found that different misalignment parameters have different influences on the electric field distributions of the beam focus spot and the output beam characteristics. The intensity distribution of the beam is mainly determined by the misalignment matrix element E, and the phase distribution is affected by the misalignment matrix elements G and E.

Characteristics of beam alignment in a high power four-pass laser amplifier.

Beam alignment is used to control the pointing, rotation, and position of a beam automatically. We give an overview of the beam alignment system for a four-pass amplifier system. The coupling relationships between dependent quantities and deviations thereof for parameters of key optical elements are analyzed using matrix optics techniques. The rotation characteristics of a near field are discussed. The characteristics of the four-pass adjustment in the cavity spatial filter are shown and the output characteristics are provided. Finally, we develop an adjustment procedure.